• Journal of Korea Multimedia Society
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• v.19 no.11
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• pp.1891-1899
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• 2016

Recently food problem and crop disaster have been increased continuously because of the meteorological changes. These cause rising cost for crops continuously and irregularly. Some researchers have studied straight structure of device for hydroponics and plant factory previously to solve a fundamental part of these problems. However, there are several problems such as limited crop cultivation space, providing irregular nutrients for crops, and lack of monitoring interfaces. For them, we propose an optimal growth and development crops management system using light source tracking and recirculation of nutrient solution method to supply nutrient continuously based on IoT. In order to evaluate the performance of our system, we compared and analyzed in terms of two viewpoints, the tracking analysis for natural light source measurement and the growth of crops through artificial light, LED, respectively. We confirmed that the higher the duty ratio of LED, the larger the crop's size, particularly. As well as, for about 1 month, we compared with the existing natural light growing environment and that of our system. It was confirmed that the size of the crops grown through our system is about three times larger than that of natural light natural crops.

• International Journal of Air-Conditioning and Refrigeration
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• v.9 no.3
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• pp.18-26
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• 2001

Environmental chamber (EC) is an experimental facility used to analyze the characteristics of thermal response of testing objects by the artificial control of weather conditions. The EC in KIFR can simulate the weather conditions by the control of temperature, humidity, and solar radiation. A two-storied testing building is located inside EC. For the exact thermal response analysis of testing building, monthly or yearly scheduled operations are necessary. Although this long term operation gives the exact experimental data, it requires a high operational cost, long duration, and lots of manpower. Therefore it is necessary to perform the shortened experiments without sacrificing the validity of the obtained results. Since the characteristics of thermal response from the shortened experiments are different from the full time results, the analytical method to analyze the thermal response from the shortened experiments to estimate a full times results is developed in this study The thermal response of testing building is performed using commercial software TRNSYS.

• KIEAE Journal
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• v.11 no.6
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• pp.127-132
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• 2011

Since the late 20th century, countries of the world have made every effort to solve environmental problems due to global warming. The Korean Government has also made various efforts on reducing energy and $CO_2$ emission under the motto of "Low-Carbon Green Growth". In order to achieve the goal to reduce energy in the construction field, severe design standards and regulations on saving energy in new buildings have been established. However, for maximizing the reduction of energy in buildings, it is time to focus on deteriorated buildings where applications of energy saving designs and techniques have been insufficient. Especially, there are little guidelines and researches on reducing energy through remodeling at deteriorated school buildings which were built over 20 years ago. This paper suggests the priority of factors to reduce energy on the remodeling process at deteriorated school buildings using the AHP(Analytic Hierarchy Process) method. For applying the AHP method, the survey of staffs in the Education Offices and board members in the Korea Institute of Ecological Architecture and Environment was conducted via e-mail. As a result, factors of insulation, daylighting, system control, and windows turned out important in the energy reducing remodeling process at deteriorated school buildings, while factors of artificial lighting, solar heating, ventilation, and system did relatively unimportant.

• KIEAE Journal
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• v.17 no.3
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• pp.45-50
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• 2017

Purpose: There have been more researches focused on eco-friendly construction practices in order to save energy consumed and these practices have been extensively applied for constructing buildings. However, researches on energy consumption saving and efficiency for hospital facilities have been still insufficient. This research aims to draw factors that affect energy efficiency of hospital buildings through literature reviews and perform an expert-survey using AHP(Analytical Hierarchy Process) method in order to analyze the importances and priorities of these energy efficient factors. Method: Using the AHP method, this paper suggests the importances and priorities of factors to affect energy efficiency in hospital buildings. The survey of experts at a architectural design and a construction management companies was conducted via e-mail and mail. Result: As a result, factors of window and door, insulation, ventilation, and natural lighting turned out relatively important as respectively 0.104, 0.102, 0.101, and 0.095 n the energy efficiency in hospital buildings, while factors of artificial lighting, geothermal, solar heat, and control did unimportant as 0.027, 0.033, 0.043, and 0.053.

• Korean Institute of Interior Design Journal
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• v.19 no.3
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• pp.22-29
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• 2010

Recent days, transition to ecological thought is being accelerating by environmental impact with a sustainable development. This symptom is no exception in architecture area. So is vernacular design affecting on modern architecture in many ways in terms of economical aspect and eco-friendly environment as well. Natural energy like solar power, environment, and terrestrial heat that applied in vernacular architecture is also widely accepted in name of 'sustainable energy' of which a design applied with ventilation and airing of natural wind is very useful & pragmatic in terms of economical reason. Accordingly, this study examined a relation between vernacular architecture and natural wind and compared it with traditional type and its feature of ventilation & airing. Ventilation & airing applied in the past can be divided into three categories: methods by convection, natural element, and architectural type. All these methods gave some pleasant felling indoors when there were no artificial energies. Even in modern age, such a ventilation & airing is being used with traditional type in different variety of materials, and it will be developed with modern technology without any extra cost in terms of sustainable expansion, and opened for further researches.

• Journal of architectural history
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• v.2 no.2 s.4
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• pp.89-106
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• 1993

Wherever Buddhism has flourished, there were stupas in the form of monuments which have their origin in the tumulm of prehistoric times. After the death of Buddha, his body was cremated following the Indian funeral custom. His ashes, which long reserved for the remains of nobles and holymen, were enshrined under such artificial hills of earth and brick. The Stupa was in origin a simple burial-mound. The form of the burial-mound was a symbolical or magic reconstruction of the imagined shape of the sky, like a dome covering the earth. The domical form of the earliest tumuli may have been concious replicas of the shape of the Vedic hut. There are relationships which may have originally existed between the stupa and West Asiatic monuments. Buddhist Stupa originally cosisted of an almost hemispherical tumulus(anda) and an altar-like structure (harmika) on its top, surmounted by one or several superimposed honorific umbrellas (hti, catta). This hemispherical form is associated with centralisation, lunar worship, mother earth, and Siva. Anda means a symbol of latent creative power, the harmika symbolizes the sanctuary enthroned aboved the world. The honorific umbrella, as an abstract imitation of the shade-giving tree is one of the chief solar symbols and that of enlightenment.

• Journal of the Korean Institute of Landscape Architecture
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• v.16 no.1
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• pp.37-42
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• 1988

For the purpose of cultivating landscape plants, the culture soil of briquet ashes and sludge cakes from urban drainages was used as a bed soil. And Taxus cuspidata, syringa vulgaris, Ligstrum obtusifolia and Buxus microphylla were selected as experimental materials on this soil. The comparison of their growth showed the following results. Each plant showed a slight difference in primary growth and two months after planting, there were notable differences between treated and control plots respectively. Syringa vulgaris shoved the highest growth and the next were Ligstrum obtusifolia and Taxus cuspidata in series. Especially Taxus cuspidata showed the lowest quantity of dry weight compared with other plants, and influenced a little by mean temperature and solar radiation. It is expected to get a high effect in landscape planting by using briquet ashes and sludge cakes.

• Journal of Korea Multimedia Society
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• v.24 no.10
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• pp.1414-1424
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• 2021

In this paper, the importance of input factors of a DNN (Deep Neural Network) PM_2.5 forecasting model using LRP(Layer-wise Relevance Propagation) is analyzed, and forecasting performance is improved. Input factor importance analysis is performed by dividing the learning data into time and PM_2.5 concentration. As a result, in the low concentration patterns, the importance of weather factors such as temperature, atmospheric pressure, and solar radiation is high, and in the high concentration patterns, the importance of air quality factors such as PM_2.5, CO, and NO₂ is high. As a result of analysis by time, the importance of the measurement factors is high in the case of the forecast for the day, and the importance of the forecast factors increases in the forecast for tomorrow and the day after tomorrow. In addition, date, temperature, humidity, and atmospheric pressure all show high importance regardless of time and concentration. Based on the importance of these factors, the LRP_DNN prediction model is developed. As a result, the ACC(accuracy) and POD(probability of detection) are improved by up to 5%, and the FAR(false alarm rate) is improved by up to 9% compared to the previous DNN model.

• International Journal of Computer Science & Network Security
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• v.21 no.2
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• pp.77-87
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• 2021

In this study, a novel improved second order Radial Basis Function Neural Network based method with excellent scheduling capabilities is used for the dynamic prediction of short and long-term energy required applications. The effectiveness and the reliability of the algorithm are evaluated using training operations with New England-ISO database. The dynamic prediction algorithm is implemented in Matlab and the computation of mean absolute error and mean absolute percent error, and training time for the forecasted load, are determined. The results show the impact of temperature and other input parameters on the accuracy of solar Photovoltaic load forecasting. The mean absolute percent error is found to be between 1% to 3% and the training time is evaluated from 3s to 10s. The results are also compared with the previous studies, which show that this new method predicts short and long-term load better than sigmoidal neural network and bagged regression trees. The forecasted energy is found to be the nearest to the correct values as given by England ISO database, which shows that the method can be used reliably for short and long-term load forecasting of any electrical system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1777-1783
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• 2021

The use of drones is gradually increasing for the efficient maintenance of large-scale renewable energy power generation complexes. For a long time, photovoltaic panels have been photographed with drones to manage panel loss and contamination. Various approaches using artificial intelligence are being tried for efficient maintenance of large-scale photovoltaic complexes. Recently, semantic segmentation-based application techniques have been developed to solve the image classification problem. In this paper, we propose a classification model using semantic segmentation to determine the presence or absence of failures such as arcs, disconnections, and cracks in solar panel images obtained using a drone equipped with a thermal imaging camera. In addition, an efficient classification model was implemented by tuning several factors such as data size and type and loss function customization in U-Net, which shows robust classification performance even with a small dataset.